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Answering Questions With Statistics
Quiz 16: Hypothesis Testing With Measures of Association and Regression
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Question 1
Multiple Choice
Your research hypothesis is that there is a negative association (as indicated by Kendall's tau-b) between social class and happiness with life. Based on the following output, the sample results are consistent with the _____, the significance level is _____, and the null hypothesis is _____. Symmetric Measures
 ValueÂ
 Asymp. Std.Â
 Error?Â
 Approx. T?Â
 Approx, Sig.Â
 Ordinal by Ordinal Kendall’s tau-bÂ
.
199
.
088
2.210
.
027
 N of Valid CasesÂ
122
\begin{array}{|l|r|r|r|r|}\hline & \text { Value } & {\begin{array}{c}\text { Asymp. Std. } \\\text { Error? }\end{array}} & \text { Approx. T? } & \text { Approx, Sig. } \\\hline \text { Ordinal by Ordinal Kendall's tau-b } & .199 & .088 & 2.210 & .027 \\\text { N of Valid Cases } & 122 & & & \\\hline\end{array}
 Ordinal by Ordinal Kendall’s tau-bÂ
 N of Valid CasesÂ
​
 ValueÂ
.199
122
​
 Asymp. Std.Â
 Error?Â
​
.088
​
 Approx. T?Â
2.210
​
 Approx, Sig.Â
.027
​
​
a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis.
Question 2
Essay
What kinds of questions can you answer using tests of significance for measures of association?
Question 3
Multiple Choice
For which of the following inferential statistics must you identify hypotheses as one-tailed or two-tailed?
Question 4
Multiple Choice
In SPSS output the significance levels for regression coefficients are not marked as one- or two-tailed. That means they are
Question 5
Multiple Choice
Which SPSS procedure would you use to answer the question "Is there a significant relationship between nationality and religious affiliation?"
Question 6
Multiple Choice
Which SPSS procedure would you use to answer the question "Does gender have a significant net effect on amount given to charity after controlling for age and personal earnings?"
Question 7
Multiple Choice
Based on this correlation matrix, which of the following is true? Correlations
 AGEÂ
 EDUCÂ
 HOURSÂ
 TVHOURSÂ
 AGEÂ
 Pearson CorrelationÂ
1
.
11
2
∘
.
22
6
∘
−
.
079
 Sig. (2-tailed) Â
.
038
.
001
.
220
Â
N
341
341
211
240
 EDUCÂ
 Pearson CorrelationÂ
.
11
2
∘
1
.
037
−
.
24
0
′
′
 Sig. (2-tailed) Â
.
038
.
593
.
000
Â
N
341
341
211
240
 HOURSÂ
 Pearson CorrelationÂ
.
22
6
∘
.
037
1
−
.
049
 Sig. (2-tailed) Â
.
001
.
593
.
560
Â
N
211
211
211
146
 TVHOURSÂ
 Pearson CorrelationÂ
.
079
−
.
24
0
′
′
−
.
049
1
 Sig. (2-tailed) Â
.
220
.
000
.
560
Â
N
240
240
146
240
\begin{array}{|ll|r|r|r|r|}\hline & \text { AGE } & \text { EDUC } & \text { HOURS } & \text { TVHOURS } \\\hline \text { AGE } & \text { Pearson Correlation } & 1 & .112^{\circ} &{.226^{\circ}} & -.079 \\& \text { Sig. (2-tailed) } & & .038 & .001 & .220 \\& \mathrm{~N} & 341 & 341 & 211 & 240 \\\hline \text { EDUC } & \text { Pearson Correlation } & .112^{\circ} & 1 & .037 & -.240^{\prime \prime} \\& \text { Sig. (2-tailed) } & .038 & & .593 & .000 \\& \mathrm{~N} & 341 & 341 & 211 & 240 \\\hline \text { HOURS } & \text { Pearson Correlation } & .226^{\circ} & .037 & 1 & -.049 \\& \text { Sig. (2-tailed) } & .001 & .593 & & .560 \\& \mathrm{~N} & 211 & 211 & 211 & 146 \\\hline \text { TVHOURS } & \text { Pearson Correlation } & .079 & -.240^{\prime \prime} & -.049 & 1 \\& \text { Sig. (2-tailed) } & .220 & .000 & .560 & \\& \mathrm{~N} & 240 & 240 & 146 & 240 \\\hline\end{array}
 AGEÂ
 EDUCÂ
 HOURSÂ
 TVHOURSÂ
​
 AGEÂ
 Pearson CorrelationÂ
 Sig. (2-tailed) Â
Â
N
 Pearson CorrelationÂ
 Sig. (2-tailed) Â
Â
N
 Pearson CorrelationÂ
 Sig. (2-tailed) Â
Â
N
 Pearson CorrelationÂ
 Sig. (2-tailed) Â
Â
N
​
 EDUCÂ
1
341
.11
2
∘
.038
341
.22
6
∘
.001
211
.079
.220
240
​
 HOURSÂ
.11
2
∘
.038
341
1
341
.037
.593
211
−
.24
0
′′
.000
240
​
 TVHOURSÂ
.22
6
∘
.001
211
.037
.593
211
1
211
−
.049
.560
146
​
−
.079
.220
240
−
.24
0
′′
.000
240
−
.049
.560
146
1
240
​
​
*. Correlation is significant at the 0.05 level (2-tailed) . *. Correlation is significant at the 0.01 level (2-tailed) .
Question 8
Multiple Choice
Your research hypothesis is that there is a positive correlation between AGE and years of schooling (EDUC) . Based on the following output, the sample results are consistent with the _____, the significance level is _____, and the null hypothesis is _____. Correlations
 AGEÂ
 EDUCÂ
 AGEÂ
 Pearson CorrelationÂ
1
.
19
0
∘
 Sig-(2-tailed) Â
.
036
Â
N
122
122
 EDUCÂ
 Pearson CorrelationÂ
−
19
0
∘
1
 Sig-(2-tailed) Â
.
036
Â
N
122
122
\begin{array}{|ll|r|r|}\hline & & {\text { AGE }} & \text { EDUC } \\\hline \text { AGE } & \text { Pearson Correlation } & 1 & .190^{\circ} \\& \text { Sig-(2-tailed) } & & .036 \\& \mathrm{~N} & 122 & 122 \\\hline \text { EDUC } & \text { Pearson Correlation } & -190^{\circ} & 1 \\& \text { Sig-(2-tailed) } & .036 & \\& \mathrm{~N} & 122 & 122 \\\hline\end{array}
 AGEÂ
 EDUCÂ
​
 Pearson CorrelationÂ
 Sig-(2-tailed) Â
Â
N
 Pearson CorrelationÂ
 Sig-(2-tailed) Â
Â
N
​
 AGEÂ
1
122
−
19
0
∘
.036
122
​
 EDUCÂ
.19
0
∘
.036
122
1
122
​
​
*. Correlation is significant at the
0.05
0.05
0.05
level (2tailed) .
Question 9
Multiple Choice
Which of the following conclusions is supported by these regression results?
 Unstandardized CoefficientsÂ
 Standardized Coefficients
 ModelÂ
 BÂ
 Std. ErrorÂ
 BetaÂ
t
 Sig.Â
1
1.873
2.512
.
746
.
456
 (Constant) Â
−
.
018
.
045
−
.
021
−
388
.
698
 AGEÂ
.
030
.
088
.
018
337
.
737
 CHILDRENÂ
.
396
.
051
.
420
7.688
.
000
 EDUCÂ
−
294
.
112
−
139
−
2.623
.
009
\begin{array}{|l|l|r|r|r|r|r|}\hline & \text { Unstandardized Coefficients }&&\text { Standardized Coefficients} \\\hline \text { Model } & {\text { B }} & \text { Std. Error } & {\text { Beta }} &{t} & \text { Sig. } \\\hline 1 & 1.873 & 2.512 & & .746 & .456 \\& \text { (Constant) } & -.018 & .045 & -.021 & -388 & .698 \\\text { AGE } & .030 & .088 & .018 & 337 & .737 \\\text { CHILDREN } & .396 & .051 & .420 & 7.688 & .000 \\\text { EDUC } & -294 & .112 & -139 & -2.623 & .009 \\\hline\end{array}
 ModelÂ
1
 AGEÂ
 CHILDRENÂ
 EDUCÂ
​
 Unstandardized CoefficientsÂ
 BÂ
1.873
 (Constant) Â
.030
.396
−
294
​
 Std. ErrorÂ
2.512
−
.018
.088
.051
.112
​
 Standardized Coefficients
 BetaÂ
.045
.018
.420
−
139
​
t
.746
−
.021
337
7.688
−
2.623
​
 Sig.Â
.456
−
388
.737
.000
.009
​
.698
​
​
Question 10
Multiple Choice
Which variable has a significant net effect on willingness to allow legal abortion (ABORTOK) ? Coefficients"
 Unstandardized Coefficients
Standardized Coeficients
 ModelÂ
 BÂ
 Std. ErrorÂ
 BetaÂ
t
 Sig.Â
1
 (Constant) Â
2.327
1.648
1.412
.
160
 AGEÂ
.
034
.
058
.
042
.
584
560
 EDUCÂ
.
100
.
064
.
117
1.560
.
120
 RELINTENÂ
−
.
729
.
202
−
.
257
−
3.606
.
000
 SIBLINGSÂ
−
.
036
.
078
−
.
034
−
.
461
.
646
\begin{array}{|ll|r|r|r|r|r|}\hline &&\text { Unstandardized Coefficients}&&\text {Standardized Coeficients}\\ \text { Model } &&{\text { B }} & \text { Std. Error } & {\text { Beta }} & {\mathrm{t}} & {\text { Sig. }} \\\hline 1 & \text { (Constant) } & 2.327 & 1.648 & & 1.412 & .160 \\& \text { AGE } & .034 & .058 & .042 & .584 & 560 \\& \text { EDUC } & .100 & .064 & .117 & 1.560 & .120 \\& \text { RELINTEN } & -.729 & .202 & -.257 & -3.606 & .000 \\& \text { SIBLINGS } & -.036 & .078 & -.034 & -.461 & .646 \\\hline\end{array}
 ModelÂ
1
​
 (Constant) Â
 AGEÂ
 EDUCÂ
 RELINTENÂ
 SIBLINGSÂ
​
 Unstandardized Coefficients
 BÂ
2.327
.034
.100
−
.729
−
.036
​
 Std. ErrorÂ
1.648
.058
.064
.202
.078
​
Standardized Coeficients
 BetaÂ
.042
.117
−
.257
−
.034
​
t
1.412
.584
1.560
−
3.606
−
.461
​
 Sig.Â
.160
560
.120
.000
.646
​
​
a. Dependent Variable: ABORTOK
Question 11
Multiple Choice
Which SPSS procedure would you use to answer the question "Is there a significant positive correlation between strength of attachment to a religion and amount given to charity?"
Question 12
Multiple Choice
Your research hypothesis is that there is an association (as indicated by Cramer's V) between race and highest educational degree. Based on the following output, the sample results are consistent with the _____, the significance level is _____, and the null hypothesis is _____.
 Symmetric MeasuresÂ
 ValueÂ
 Approx, Sig.Â
 Nominal by NominalÂ
 PhiÂ
.
278
.
000
 Cramer’s VÂ
.
196
.
000
N
 of Valid CasesÂ
450
\begin{array}{l}\text { Symmetric Measures }\\\begin{array} { | l l | r | r | } \hline & & \text { Value } & \text { Approx, Sig. } \\\hline \text { Nominal by Nominal } & \text { Phi } & .278 & .000 \\& \text { Cramer's V } & .196 & .000 \\ { \mathrm { N } \text { of Valid Cases } } & & 450 & \\\hline\end{array}\end{array}
 Symmetric MeasuresÂ
 Nominal by NominalÂ
N
 of Valid CasesÂ
​
 PhiÂ
 Cramer’s VÂ
​
 ValueÂ
.278
.196
450
​
 Approx, Sig.Â
.000
.000
​
​
​
Question 13
Multiple Choice
Which SPSS procedure would you use to answer the question "Do the countries of North America, South America, Europe, and Oceania significantly differ in average national life expectancy?"